IT Solutions Engineer

Axelon

  • San Francisco, CA
  • 4 days ago
  • $100–$150 Per Hour

Highlights

Knowledge of data pipeline orchestration, data integration frameworks, SQL, and data modeling concepts. Skills in program planning, governance, budget, and resource management, as well as risk and dependency management.

Numbers & Facts

LocationSan Francisco, CA
Salary$100–$150 Per Hour

Description

Summary:

  • Duration: 4 Months
  • Work Mode: 90% Remote
  • Location: San Francisco, CA (Managers prefer local candidates)

Responsibilities:

  • Manage complex technology or data-driven projects.
  • Lead enterprise data platform implementations.
  • Deliver projects involving Snowflake, Palantir Foundry, and Ataccama.
  • Oversee data engineering and data management solutions.
  • Manage cross-functional technical teams.
  • Work within Agile and Waterfall delivery frameworks.

Requirements:

  • Bachelor’s degree in Computer Science, Information Systems, Engineering, Data Science, or a related field. Master’s degree preferred.
  • Minimum 8 years of experience managing complex technology or data-driven projects.
  • Minimum 5 years of experience leading enterprise data platform implementations.
  • Experience with Snowflake, Palantir Foundry, and Ataccama.
  • Proficiency in cloud data platforms (AWS, Azure, or GCP).
  • Expertise in data engineering, ETL/ELT development, data warehouse and lakehouse architectures.
  • Knowledge of data pipeline orchestration, data integration frameworks, SQL, and data modeling concepts.
  • Experience in data governance and quality, including Master Data Management, Data Quality Management, Metadata Management, and Data Governance Frameworks.
  • Proficiency in project management tools like Jira, Azure DevOps, or similar.
  • Skills in program planning, governance, budget, and resource management, as well as risk and dependency management.

Preferred Skills:

  • PMP, PgMP, Scrum Master, SAFe Agilist, or equivalent certification.
  • Experience in enterprise utility, energy, healthcare, financial services, or large-scale regulated industries.
  • Knowledge of data privacy and compliance frameworks.
  • Experience with DevOps and DataOps practices.
  • Familiarity with AI/ML enablement through enterprise data platforms.

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